ABC of EMG.pdf

The ABC of EMGA Practical Introductionto Kinesiological ElectromyographyPeter Konrad Version 1.0 April 2005Noraxon INC. USA.Powered by:NORAXON U. S. A. , I NC.ABC of EMG – A Practical Introduction to Kinesiological ElectromyographyPage 2Contents:SIGNAL ORIGIN AND ACQUISITIONINTRODUCTION most of the surface EMG frequency power is located between 10 and 250 Hz. This power distributioncan be calculated by the “Fast Fourier Transformation” (FFT) and graphically presented as a Total PowerSpectrum of the EMG signal (Fig. 31), which shows the frequency power distribution (Y-axis) in ratio to thefrequency band (X-axis).The precise shape of the total power spectrum canvary widely, depending on the FFT-settings and themeasurement conditions (especially muscle type,muscle length and tissue/skin filter effects). To per-form a signal check test, ask your subject to contractthe investigated muscle against static resistance(about 40 – 60 % of the perceived maximum contrac-tion level) and measure a 3 –5 second EMG portion.When stored, select an analysis interval, e.g. 1 sec-ond and start a power spectrum analysis. Investigatethe characteristics of the spectrum:- step increase from the high pass (10Hz)- the peak frequency is typically located between 50 and 80 Hz- from here the spectrum curves decreases and reaches zero between 200 and 250 Hz- observe if untypical power peaks are visible, especially outside the band-range- check if a dominant power peak is visible at 50 (EU) or 60 (USA) Hz.The total power spectrum can easily identify power hum contaminating the EMG baseline (Fig. 32) and givesa clear separation to an increased EMG activity which may appear if a subject is not able to relax a muscle.Fig. 31: The total power spectrum of a surface EMG recording: most of the signal power is located between 10 and 250 Hz.Fig. 32: The total power spectrum of a hum contaminated EMG recording: The high power peak at 50 Hz identifies the noise contamination of the recording, typically due to in- creased electrical ground noise of the power net within the selected room (also see fig. 33)ABC of EMG – A Practical Introduction to Kinesiological ElectromyographyPage 24EMG ArtifactsDue to its sensitive nature (signal range starts from a few microvolts) the EMG signal can be influenced byexternal noise sources or other artifact sources. Most of them can easily be avoided if the previously men-tioned guidelines of proper skin preparation and electrode position are checked. To give a better picture ofpossible disturbances, the following graphs show some typical noise or artifact contaminated signals.Interfering power hum An EMG amplifier can “catch” ground noise from the power net which results in increased baseline noise (50/60 Hz noise – Fig. 33). If the electrode was applied properly, in most cases another device (with poor electrical grounding) causes this problem. To solve it correctly, ground all devices, especially when equipped with electro-motors (treadmills, training machines, isokinetics machines etc…). Also try to change the power plug and always try to avoid multiple plug connec- tors and cable drums for the EMG amplifier.Baseline offsetThis constant EMG - baseline shift may occur if any change within the application site was done after the auto-calibration or if the subject did not relax at measurement start (Fig. 34). Use an “Offset correction” function to correct this shift before you record your data.Baseline shiftsAny regular EMG burst returns to zero within a few milli-seconds, the EMG rest-line stays at constant zero. Any visible shift > 5 ms indicates an artifact (Fig. 35). This typically occurs if the cables shake too much or if the volume distance between the muscle belly and electrode site is changed by e.g. external lever arm forces (bad cable fixation) or lo- cal pressure. In jump testing, you may see similar base shifts due to heavy dislocation of the muscle belly (muscle wobbling due to impact forces) Proper electrode/cable fixation and very good skin preparation can solve these problems.ECG artifactsWhenever you measure near the heart (shoulder and trunk muscles on the left side), ECG bursts may contaminate the EMG recording (Fig. 36). This is a biological artifact that often cannot be avoided. It can be reduced by very good skin preparation and modified position of the ground electrode. State of the art signal processing routines can “clean” these bursts without destroying the regular EMG characteris- tics (see chapter Signal Processing ECG Reduction).Fig. 33: EMG raw recording contaminated by power hum noiseFig. 34: EMG raw recording with offset shift to plusFig. 35: EMG raw recording with cable movement artifactsFig. 36: EMG raw recording with ECG spikesABC of EMG – A Practical Introduction to Kinesiological ElectromyographyPage 25Prepare EMG - Action listAction / StepComments1. Ask your subject to wear appropriate clothesYou need access to muscles which may be covered by pants, etc. Too stiff clothes on the electrodes may produce artifacts2. Decide for a “navigation” technique to identify the electrode location and landmark promi- nent regionsUse a pen to mark landmarks and orientation lines. Use a flexible scale band to measure distances. Follow the e.g. SENIAM guidelines.3. Clean the skin with abrasive /conductive fluidEasiest and fastest method! Alternatively: very good alcohol cleaning4. Attach electrodes parallel to muscle fibers at typically 2cm electrode distance, use the smallest electrode type availableIf possible avoid motor endplates (static tests) and select middle belly portions to increase selectivity and decrease the risk of muscle belly dislocation5. Wait at least 3 minutes and use the time to stretch, warm up or prepare your subjectThe electrode to skin contacts need some time to reach a stable electrical (impedance) condition. Beginners may want to check the electrode impedance6. Connect and fixate cablesFor dynamic movements fixate all leads, leaving enough freedom to avoid lever forces on the electrodes7. Ask your subject to lay down on a bench and relaxSimilar positions like laying on the ground or sitting may work well too8. Start the signal monitor and check each EMG trace: Baseline check!Check noise level, zero offset and possible shifts within joint movement9. Check EMG activity bursts: do I see EMG?By using manual muscle tests, the general appearance of EMG bursts should be checkedABC of EMG – A Practical Introduction to Kinesiological ElectromyographyPage 26Signal Processing - RectificationGeneral commentsThe raw EMG recording already contains very important information and may serve as a first objective infor-mation and documentation of the muscle innervation. The “off-on” and “more-less” characteristics and otherqualitative assessments can directly be derived and give an important first understanding of the neuromus-cular control within tests and exercises. If a quantitative amplitude analysis is targeted in most cases someEMG specific signal processing steps are applied to increase the reliability and validity of findings. By scien-tific recommendation (ISEK, SENIAM) the EMG recording should not use any hardware filters (e.g. notch fil-ters), except the amplifier bandpass (10 – 500 Hz) filters that are needed to avoid anti-aliasing effects withinsampling. At best case, the post hoc processing can be removed at any time to restore the raw data set.Some of the well established processing methods are introduced in the following chapters.Full wave rectificationIn a first step all negative amplitudes are converted to positive amplitudes, the negative spikes are “movedup” to plus or reflected by the baseline (Fig. 37). Besides easier reading the main effect is that standard am-plitude parameters like mean, peak/max value and area can be applied to the curve (raw EMG has a meanvalue of zero).Fig. 37: EMG raw recording with ECG spikesABC of EMG – A Practical Introduction to Kinesiological ElectromyographyPage 27Signal Processing - SmoothingGeneral commentsAs stated above the interference pattern of EMG is of random nature - due to the fact that the actual set ofrecruited motor units constantly changes within the diameter of available motor units and the way they motorunit action potentials superpose is arbitrary. This results in the fact that a raw EMG burst cannot be repro-duced a second time by its precise shape. To address this problem, the non-reproducible part of the signal isminimized by applying digital smoothing algorithms that outline the mean trend of signal development. Thesteep amplitude spikes are cut away; the signal receives a “linear envelope”. Two algorithms are established:Moving average (Movag)Based on a user defined time window, a certain amount of data are averagedusing the gliding window technique. If used for rectified signals it is also called the Average RectifiedValue (AVR) and serves as an “estimator of the amplitude behavior” (SENIAM). It relates to informationabout the area under the selected signal epoch (Fig. 38).Root Mean Square (RMS)Based on the square root calculation, the RMS reflects the mean power of thesignal (also called RMS EMG) and is the preferred recommendation for smoothing (2, 3).Both algorithms are defined for a certain epoch (time window) and typically in kinesiological studies time du-ration of 20 ms (fast movements like jump, reflex studies) to 500 ms (slow or static activities) are selected. Avalue that works well in most conditions is between 50 and 100 ms. The higher the time window is selected,the higher the risk of a phase shift in contractions with steep signal increase needs to be considered (see redrectangle in Fig. 38).Movag at 300 msRMS at 300 msFig. 38: Comparison of two smoothing algorithms using the same window width: Being very similar in shape, the RMS algo- rithm (lower trace) shows higher EMG amplitude data than the MovAg (upper trace)ABC of EMG – A Practical Introduction to Kinesiological ElectromyographyPage 28Signal Processing - Digital FilteringGeneral commentsWith the exception of amplifier bandpass filtering additional filtering is not needed in regular kinesiologicalEMG studies (performed with modern amplifier technology). Scientific recommendations for research studies(SENIAM, ISEK) deny any narrower band setting and the target is to measure the EMG in the full band lengthof 10 to 500 Hz. Especially any type of notch filter (to e.g. cancel out 50 or 60 Hz noise) is not accepted be-cause it destroys too much EMG signal power. Biofeedback units working with heavily preprocessed signalsshould not be used for scientific studies.Application of filters in EMGIn certain situations, it may be suitable to apply additional digital filters. Alternatively to Movag and RMSsmoothing, a low pass filter at 6 Hz (e.g. Butterworth, 2nd order or higher – see Fig. 39) can be used to cre-ate a linear envelope EMG (11). One benefit of higher order digital filters is that it can be applied recursivelyto minimize the phase shift phenomenon mentioned in the previous chapter.Fine wire studies may suffer from the wire movement artifacts within dynamic studies (see Fig.22). They oftencan be minimized by applying a high pass filter at 20 – 25 Hz (See chapter Fine wire electrodes). Such a filtersetting does not significantly change the ensemble average curves e.g. typically processed in gait studies(see chapter Average EMG / Ensemble Average). The use of vaginal or anal probes can be improved bysetting high pass filters to stabilize baseline shifts due to instable contact between probe and muscle /skinsurface. Finite Impulse Response filter (FIR) and Infinite Impulse Response Filter (IIR) with several subclasses (window edge fading) exist and specialists may identify optimal filter settings and coefficients to bestfit a signal to a given purpose. Otherwise, the rectified RMS smoothed EMG signal without any additional fil-tering can be considered as a standard processing in kinesiological EMG.Fig. 39: Comparison of three smoothing algorithms and their effect on amplitude shape and statistics. The 6 Hz Butterworth Low Pass filter (lowest channel) compares to a MovAg with 100ms window width. Both show the same shape and identical amplitude parametersABC of EMG – A Practical Introduction to Kinesiological ElectromyographyPage 29Signal Processing – Amplitude NormalizationGeneral commentsOne big drawback of any EMG analysis is that the amplitude (microvolt scaled) data are strongly influencedby the given detection condition (see chapter Influence of Detection Condition): it can strongly vary betweenelectrode sites, subjects and even day to day measures of the same muscle site. One solution to overcomethis “uncertain” character of micro-volt scaled parameters is the normalization to reference value, e.g. themaximum voluntary contraction (MVC) value of a reference contraction. The basic idea is to “calibrate the mi-crovolts value to a unique calibration unit with physiological relevance, the “percent of maximum innervationcapacity” in that particular sense. Other methods normalize to the internal mean value or a given trial or to theEMG level of a certain submaximal reference activity. The main effect of all normalization methods is that theinfluence of the given detection condition is eliminated and data are rescaled from microvolt to percent of se-lected reference value. It is important to understand that amplitude normalization does not change the shapeof EMG curves, only their Y-axis scaling!The concept of MVC NormalizationThe most popular method is called MVC-normalization, referring to a Maximum Voluntary Contraction doneprior to the test trials (Fig. 40).Typically, MVC contractions are performed against static resistance. To really produce a maximum innerva-tion, a very good fixation of all involved segments is very important. Normal (untrained) subjects may haveproblems producing a true MVC contraction level, not being used to such efforts.Logically, patients cannot (and should) not perform MVCs with injured structures and alternative processingand analysis methods must be considered. Concentrating on treatment issues, a clinical concept would workwith the “acceptable maximum effort” (AME) which serves as a guideline for biofeedback oriented treatmentregimes. One cannot consider an AME as a MVC replacement which can strongly differ from day to day.Microwolt% MVCMVC100%Test TrialsStatic TestMicrowolt% MVCMVC100%Test TrialsStatic TestFig. 40: The concept of MVC normalization. Prior to the test/exercises a static MVC contraction is performed for each muscle. This MVC innervation level serves as reference level (=100%) for all forthcoming trialsABC of EMG – A Practical Introduction to Kinesiological ElectromyographyPage 30The practice of MVC NormalizationThe MVC test has to be performed for each investigated muscle separately. The first step is to identify an ex-ercise/position that allows for an effective maximum innervation (not force output!